Readme
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README.md
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<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
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### Out-of-Scope Use
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## Bias, Risks, and Limitations
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1. Model may not be 100% accurate always but we are
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## How to Get Started with the Model
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<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
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With the advent of chatGPT , professionals and organizations use public chat interfaces for various applications. This often leads to leakage of PII data which causes privacy issues as users enter names , dates or even API keys etc to give the model better context. With the PII class tags, these confidential information can be masked out as class tags which enable the the end models to understand context without data leaving the server. Even developers or teams building applications with the help of third party API's can use these models for better privacy. The image below illustrates this:
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The PII model shouldn't add too much latency and be able to take in long documents, therefore we used the Qwen 0.5B as the base model. We do have larger models in house with better performance. We have coverage for south east asian langauges as well as giving the user the ability to define custom user classes as part of our plans.
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### Out-of-Scope Use
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## Bias, Risks, and Limitations
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1. Model may not be 100% accurate always but we are working on it.
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## How to Get Started with the Model
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